Retrieve a Single Value From A DataFrame

To explore the different ways to retrieve a single value from a pandas DataFrame, we'll be looking at a DataFrame of different NBA basketball teams.

import pandas as pd

# Creates a DataFrame with 'state', 'valuation', and 'championships' columns:
df = pd.DataFrame([
  {'team': 'Chicago Bulls', 'state': 'Illinois', 'valuation': 3650000000, 'championships': 6},
  {'team': 'Golden State Warriors', 'state': 'California', 'valuation': 5600000000, 'championships': 6},
  {'team': 'Los Angeles Lakers', 'state': 'California', 'valuation': 5500000000, 'championships': 17}, 
  {'team': 'Boston Celtics', 'state': 'Massachusetts', 'valuation': 3100000000, 'championships': 17}, 
  {'team': 'Miami Heat', 'state': 'Florida', 'valuation': 1750000000, 'championships': 3},
])

# Set the row label indexes to use the "team" column:
df.set_index('team', inplace = True)
df
statevaluationchampionships
team
Chicago BullsIllinois36500000006
Golden State WarriorsCalifornia56000000006
Los Angeles LakersCalifornia550000000017
Boston CelticsMassachusetts310000000017
Miami HeatFlorida17500000003
Creating a DataFrame

Retrieve a Single Value using at

A common function used to retrieve single values from a DataFrame is the at function, which uses a label pair of row and column to specify the cell.

This function only accepts row labels (e.g. Chicago Bulls) as its input. This means that integers (e.g. 0) are treated as row labels, not index positions. For this function, the row label must come first, followed by the column label.

# 'Chicago Bulls' is the row label and 'valuation' is the column label 
df.at['Chicago Bulls', 'valuation']

3650000000

Retrieving a Value Using the `at` Function

In addition to getting values, we can use the at function to change the value stored in a cell.

For example, the Golden State Warriors won the 2021-2022 NBA Championship, and the team now has 7 championship titles:

# 'Golden State Warriors' is the row label and 'championships' is the column label
df.at['Golden State Warriors', 'championships'] = 7
Setting a Value Using the `at` Function

Now, the Golden State Warriors' championships column contains the value 7 instead of 6:

# printing df
df
statevaluationchampionships
team
Chicago BullsIllinois36500000006
Golden State WarriorsCalifornia56000000007
Los Angeles LakersCalifornia550000000017
Boston CelticsMassachusetts310000000017
Miami HeatFlorida17500000003
Printing DataFrame Changes

Retrieve a Single Value using iat

Another way to retrieve a single value from a pandas DataFrame is to use the iat function.

The iat function is similar to the at function, except that it only accepts integers indexes (e.g. 0, 1...) as its input.

# 4 is the row index position and 2 is the column index position
df.iat[4, 2]

3

Retrieving a Value Using the `iat` Function

Retrieve a Single Value using loc

We can also find a single cell value using the loc function to specify the row using a label followed by the column label enclosed in brackets ([]):

# 'Boston Celtics' is the row label and 'state' is the column label
# using the loc function
df.loc['Boston Celtics']['state']

Massachusetts

Retrieving a Value Using the `loc` Function and Brackets

Retrieve a Single Value using iloc

We can also use integer positions instead of labels to specify the row. To do this, we would use the iloc function:

# 0 is the row index and 'championships' is the column label
# using the iloc function
df.iloc[0]['championships']

6

Retrieving a Value Using the `iloc` Function and Brackets

Pandas Documentation

Click Here for the full pandas documentation for the at function
Click Here for the full pandas documentation for the iat function